Vetted Tableau Professionals

“Telecom (Verizon) AI/ML practitioner who built a production multimodal system that ingests messy customer issue reports (calls, chats, emails, screenshots, videos) and turns them into confidence-scored incident summaries with reproducible steps and evidence links. Also built KPI/alarm-to-ticket correlation to rank likely root-cause domains (RAN/Core/Transport), cutting triage from hours to minutes and improving MTTR.”

“Machine Learning Intern at Docsumo who delivered a customer-facing fraud-detection solution end-to-end: rebuilt the pipeline, deployed a Random Forest model, and shipped a Python/Flask microservice on AWS SageMaker. Drove measurable production impact (precision +30%, processing time cut in half, manual review -60%, customer satisfaction +15%) and demonstrated strong customer integration and live-incident response skills.”

“AI/ML engineer with forensic analytics and healthcare claims experience (Optum), building production LLM/RAG systems to surface context-driven fraud patterns from unstructured claim notes and explain risk to investigators. Strong in large-scale retrieval performance tuning, legacy API integration with reliability patterns (SQS, circuit breakers), and MLOps orchestration on Airflow/Kubernetes with rigorous testing, monitoring, and stakeholder-friendly interpretability.”

“Recruiting Operations leader with 10 years across transportation, staffing, and tech, managing teams up to 40 in both remote-first and onsite settings. Known for rebuilding end-to-end recruiting workflows (interviewing, pay equity/salary transparency, onboarding automation) and delivering measurable outcomes including 140% revenue growth, plus strong ATS analytics and HRIS/LMS implementation experience (Workable, SmartRecruiters, Paycom, Litmos).”

“IBM engineer who built and deployed a production RAG-based LLM assistant using LangChain/FAISS with a fine-tuned LLaMA model, served via FastAPI microservices on Kubernetes, achieving 99%+ uptime. Demonstrates strong practical expertise in reducing hallucinations (semantic chunking + metadata-driven retrieval) and managing latency, plus mature MLOps practices (Airflow/dbt pipelines, MLflow tracking, monitoring, A/B and shadow deployments) and effective collaboration with non-technical stakeholders.”

“Built a production multimodal LLM-based vendor risk assessment platform that ingests SOC reports and other documents, uses a strict RAG pipeline with grounded evidence (page/paragraph citations), and dramatically reduces analyst review time. Experienced with LangGraph/LangChain/AutoGen for stateful, fault-tolerant agent workflows, and emphasizes reliability (schema validation, guardrails) plus low-latency delivery (~1–2s) through hybrid retrieval, reranking, caching, and model tiering.”

“At CVS Health, the candidate productionized a RAG-based LLM solution in a regulated healthcare setting, emphasizing reliable data pipelines, LoRA fine-tuning, monitoring, safety guardrails, and A/B testing. They have hands-on experience troubleshooting real-time RAG failures (e.g., chunking/embedding issues) and regularly lead developer-focused demos/workshops while translating technical architecture into business value for stakeholders.”

“Operations-focused advisor/operator who helps early-stage and scaling companies create alignment and execution rigor through OKRs, integrated tool stacks (Asana/Slack/HubSpot/Salesforce), and KPI/BI dashboards. Notably improved a mid-sized e-commerce company’s order fulfillment efficiency by 30% by automating data flow between sales and logistics via an integrated inventory management system, and mentors non-ops founders using a 'Translate–Simplify–Empower' model.”

“Data engineer (~4 years) with full-stack delivery experience (Next.js App Router/TypeScript + React) building a real-time operations monitoring dashboard backed by Kafka and orchestrated data pipelines. Strong production focus: Airflow + CloudWatch monitoring, automated Python/SQL validation (99.5% accuracy), and CI/CD with Jenkins/Docker; has delivered measurable improvements in latency, pipeline reliability, and query performance (Postgres/Redshift).”

“Data engineer focused on sales/marketing analytics pipelines, owning ingestion from CRMs/ad platforms through warehouse serving and dashboards at ~hundreds of thousands of records/day. Built reliability-focused systems including dbt/SQL/Python data quality gates with alerting, a resilient web-scraping pipeline (retries/backoff, anti-bot tactics, schema-change detection, backfills), and a versioned internal REST API with caching and strong developer usability.”

“Accenture consultant who shipped an LLM-based production solution during a client cloud migration to parse application code and identify only the database objects actually used, cutting migration time by 30% and accelerating realization of cloud cost benefits. Emphasizes production robustness with timeouts/retries/fallback routing, validation, observability, and a disciplined eval/monitoring loop that turns failures into regression tests.”

Bhakti Patel

Screened

Senior Full-Stack Software Engineer specializing in .NET, Python, and cloud-native systems

Worcester, MA11y exp

“Full-stack engineer who owned an end-to-end production feature for a Piraeus Bank stock exchange module, spanning React/TypeScript, backend services, and cloud operations with Docker + CI/CD, delivering reported 90% faster API responses and improved uptime. Also built a Smartwound research MVP on AWS, creating a Python image-processing/scoring pipeline to ship despite unclear image-analysis specs.”

Aishwarya Thorat

Screened

Intern Data Scientist specializing in ML engineering and LLM agentic workflows

San Francisco, CA6y exp

“Built an agentic, multi-step LLM system that generates full-stack code for API integrations using LangChain orchestration, Pinecone/SentenceBERT RAG, and a human-in-the-loop feedback loop for iterative code refinement. Also collaborated with non-technical content writers and PMs during a Contentstack internship to deliver a Slack-based AI workflow that generates and brand-checks articles with one-click approvals.”

Gabriel Hatewa

Screened

Senior Customer Success Engineer specializing in SaaS and FinTech client solutions

San Francisco, CA8y exp

“AppSec-focused customer-facing practitioner with Worldpay experience advising clients on fraud reduction via stronger transaction validation and monitoring, translating technical controls into quantified business risk to secure buy-in. Has quickly learned and supported SonarQube in production by integrating it into CI/CD and guiding remediation, and has implemented security integrations in Kubernetes with secrets management and observability while resolving RBAC/network policy issues.”

Srikanth Reddy

Screened

Mid-level AI/ML Engineer specializing in GenAI and financial risk & compliance analytics

Plainsboro, NJ7y exp

“Built and deployed a production LLM-powered financial risk and compliance platform to reduce manual trade exception handling and speed up insights from regulatory documents. Implemented a LangChain multi-agent workflow with structured/unstructured data integration (Redshift + vector DB) and emphasized hallucination reduction for regulatory safety using Amazon Bedrock. Strong MLOps/orchestration background across Kubernetes, Airflow, Jenkins, and monitoring/testing with MLflow, Evidently AI, and PyTest.”

Laasya Muktevi

Screened

Intern Machine Learning Engineer specializing in forecasting, NLP, and RAG systems

San Jose, CA5y exp

“Intern who built and deployed a production LLM-powered contract analysis system for finance teams: Azure Document Intelligence for text/table extraction plus Gemini prompting to surface key terms and risks via an async API and simple UI. Emphasizes reliability in production with fallbacks, guardrails against hallucinations, and operational concerns like latency/cost/versioning, delivering summaries in under 30 seconds instead of hours.”

Corbin Ward

Screened

Junior Product Manager / APM specializing in data tools, CMS platforms, and AI-enabled products

San Jose, CA1y exp

“Data Software Tools Analyst at Q.ai through rapid growth and a $2B Apple acquisition who led an internal CMS for participant/PII workflows using Next.js (App Router) + FastAPI/Postgres with strong security controls (JWT + Postgres RLS). Also drove a major frontend architecture shift toward React Server Components, reporting ~4x faster page loads, and has experience building durable realtime collaboration systems with Supabase/SvelteKit and server-centric state management.”

“Founder/outbound sourcing professional who builds high-trust pipelines through network-driven outreach, LinkedIn research, and in-person community events, then nurtures prospects with low-pressure, transparent multi-call processes. Created and used a custom Salesforce module to track founder candidates, manage stages, and run disciplined follow-up cadences with strong internal/external communication.”

“Analytics-focused candidate with experience building SQL/Python pipelines and dashboards for donor, campaign, and website performance reporting. They have worked with messy multi-source data, standardized metric definitions, and delivered automated reporting that reportedly reduced manual effort by about 80%.”

Atharv Sankpal

Screened

Mid-level Data Analyst specializing in financial and healthcare analytics

Baltimore, MD4y exp

“Analytics professional with experience at JPMorgan and Deloitte, focused on financial and risk data. They stand out for building scalable SQL/Python data pipelines, KPI and forecasting dashboards, and retention/cohort metrics that improved reporting reliability, forecast accuracy, and planning speed.”

“Healthcare analytics professional with TCS/Humana experience turning messy claims and eligibility data into reliable reporting assets using SQL and Python. They combine strong data engineering and analytics execution with stakeholder management, including automating monthly claims reporting from half a day to under 5 minutes and driving a provider outreach effort that reduced claim rejection rates by about 20%.”

“Analytics professional with healthcare experience at United Health Group, focused on turning messy claims and transaction data into reliable reporting assets. They combine SQL, Python, and Power BI to automate analysis, define operational KPIs, and build dashboards that improved stakeholder visibility and helped reduce processing time by about 22%.”

“Outbound-focused candidate with experience spanning EV charging/business development and e-commerce agency outreach. They combine cold calling, digital marketing, and message testing to generate qualified conversations, including booking local business owners to speak with a CEO about EV charger installation and app-host partnerships.”

“Hospitality SaaS implementation leader with experience delivering PMS, CRM, booking engine, and data integration projects for customers ranging from boutique hotels to enterprise groups with 460 locations. At Otelier, they managed 15-20 concurrent enterprise implementations and led a 460-property PMS migration, combining strong governance, executive communication, and hands-on coordination across time zones.”